Pengembangan Karakterisasi Gelembung Mikro Menggunakan Metode PIV beserta Pemantauan dengan IOT

The development of microbubble technology has been widely used in various fields. One of these areas is sterilization technology using microbubbles to speed up and increase the effectiveness of the sterilization process. One example is room sterilization using vaporized ozone gas microbubbles which can minimize the spread of the Covid-19 virus. However, research and development of microbubbles are still not much related to the characterization of their size and hydrodynamic properties. In this study, we propose the development of a continuous characterization of the size of microbubbles using the image analysis method. Image analysis aims to find the displacement vector using particle image velocimetry (PIV) techniques. The Hadamard-Rybczynski equation was used to calculate the size of the microbubbles based on the rising velocity vector of the microbubbles. The image capture process uses an LED light shadow technique to get a brighter and more stable image. The template matching algorithm is used to speed up the displacement vector analysis process used in the PIV technique. The analysis process is carried out in-situ in parallel processing using the python program on the raspberry pi4 unit. The analysis process uses three program services that run parallel, namely recording, pre-processing, and processing services. The measurement process uses three validations, namely pixel validation, template matching algorithm validation, and interrogation window. Bubble size data is displayed in the form of real-time graphs and size distribution histograms online using IoT. The test results show the size distribution of the microbubbles produced has an average of 14.60 µm with a deviation value of 0.11µm